Atomic-level, large-scale structure prediction of G protein-coupled receptors

说明/项目摘要 G蛋白偶联受体(GPCRs)是最大的整合膜蛋白家族。 几乎在每个真核细胞中都存在，将细胞外信号(配体结合)转化为 细胞内信号(G蛋白激活)。这一重要的生理作用使它们成为 重要的药物靶点，约占当今现代医学的一半 毒品。显然，GPCRs的3D结构将为以下方面提供基本的原子级信息 阐明分子组织和药物数据库的有效虚拟筛选。然而， 除了最近解决的人类β2-雄激素能受体，目前还不可能 获取其他人类GPCRs的实验结构信息。在最近取得成功的基础上 用于降级GPCR建模的线程装配精化(Tasser)算法，这 一项提案旨在为实验的产生开发新的计算方法- 经过验证的原子级GPCR型模型。重点将放在五个具有重要药学意义的家族上 包括肾上腺素、趋化因子、多巴胺、组胺和毒扁豆碱乙酰胆碱。 该项目的具体目标是：(1)开发和确定新的gpr-tasser的基准 原子级gpr蛋白质结构建模算法。(2)开发和优化 复合原子和还原的GPCR势。(3)推广GPCR-Tasser算法 公开使用和检验。(4)GPCR-TASTER在药学研究中的应用 GPCRs。(5)与实验合作者一起对GPCR模型进行验证和改进。 长期目标是(A)开发一套计算机算法，用于自动和原子- GPCR级结构预测(B)将该方法扩展到蛋白质组尺度结构建模 对于UniProt数据库中的所有GPCRs(C)，为公众可访问的GPCRs建立中央储存库 算法和结构化数据库，旨在最终缓解 生物学和医学界提供详细的原子GPCRs结构。

Description/Project Summary G protein-coupled receptors (GPCRs) are the largest family of integral membrane proteins that occur in nearly every eukaryotic cell to transduce an extracellular signal (ligand binding) into an intracellular signal (G protein activation). This essential physiological role makes them the most important pharmaceutical targets which comprise approximately half of today's modern medicinal drugs. Clearly, 3D-structures of GPCRs would provide essential atomic-level information for elucidating the molecular organization and for efficient virtual screening of drug databases. However, except for the recently solved human beta2-andrenergic receptor, it has not yet been possible to obtain experimental structural information for other human GPCRs. Building on the recent success of the threading assemble refinement (TASSER) algorithm for reduced-level GPCR modeling, this proposal seeks to develop new computational methodologies for the generation of experiment- validated, atomic-level GPCR models. The focus will be on five pharmaceutically important families including Adrenergic, Chemokine, Dopamine, Histamine, and Muscarinic acetylcholine. Specific aims of the project are: (1) Development and benchmarking of a new GPCR-TASSER algorithm for atomic-level GPCR protein structure modeling. (2) Development and optimization of composite atomic and reduced GPCR potentials. (3) Dissemination of GPCR-TASSER algorithm for public use and examination. (4) Application of GPCR-TASSER to the pharmaceutically important GPCRs. (5) Validation and refinement of the GPCR models with experiment collaborators. The long-term goals are (a) to develop a set of computer algorithms for automated and atomic- level GPCR structure prediction (b) to extend the methodology to proteomic-scale structure modeling for all GPCRs in UniProt database (c) to construct a central repository for publicly-accessible GPCR algorithms and structure databases which are designed to eventually alleviate the urgent need in biology and medical communities for the detailed atomic GPCR structures.